def 			lowercase(	UpperCamelCase_ = 4000000       )		->	int:







 '''simple docstring'''
 UpperCamelCase			  =      [0, 1]
 UpperCamelCase			  =      0
 while fib[i] <= n:
  fib.append(fib[i] + fib[i + 1]       )
  if fib[i + 2] > n:
   break
  i += 1
 UpperCamelCase			  =      0
 for j in range(len(UpperCamelCase_       ) - 1       ):
  if fib[j] % 2 == 0:
   total += fib[j]

 return total


if __name__ == "__main__":
     print(F'''{solution() = }''')

import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
     import jax
@require_flax
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase  ,     unittest.TestCase		):
   __lowerCAmelCase           =				FlaxAutoencoderKL







   @property
   def 						lowerCamelCase_	(     self						:						Tuple				):





    """simple docstring"""


    UpperCamelCase			  =      4
    UpperCamelCase			  =      3
    UpperCamelCase			  =      (32, 32)

    UpperCamelCase			  =      jax.random.PRNGKey(0				)
    UpperCamelCase			  =      jax.random.uniform(lowerCamelCase_   ,   ((batch_size, num_channels) + sizes)				)

    return {"sample": image, "prng_key": prng_key}







   def 						lowerCamelCase_	(     self						:						str				):





    """simple docstring"""


    UpperCamelCase			  =      {
        """block_out_channels""": [32, 64],
        """in_channels""": 3,
        """out_channels""": 3,
        """down_block_types""": ["""DownEncoderBlock2D""", """DownEncoderBlock2D"""],
        """up_block_types""": ["""UpDecoderBlock2D""", """UpDecoderBlock2D"""],
        """latent_channels""": 4,
    }
    UpperCamelCase			  =      self.dummy_input
    return init_dict, inputs_dict
